As a means to summarize various accomplishments in the field of RNA structure Stuart Le Grice (CCR) and myself edited a special edition of the Methods journal entitled Advances in RNA Structure Determination. The edition included 19 contributions, including one from my group, each describing various methodologies used in RNA structure prediction and analysis. Examples of contributions included descriptions of methods for labeling RNAs at specific sites, the use of small angle x-ray scattering and atomic force microscopy, the use of SHAPE, hydroxyl radical footprinting, FRET, aptamer development, computational methodologies including coarse-grained simulation techniques, RNA folding and 3D structure prediction, a database of RNA motifs and a method for generating RNA-based nanorings. The issue is quite comprehensive, covering the current state of the art of RNA structure. Our previous discovery of the structure of the turnip crinkle virus tRNA-like translational enhancer (TCV TSS) has permitted us to pursue the use of a relatively new technique for understanding the structural characteristics of an RNA when optical tweezers are applied to pull the molecular structure apart. Essentially a force is applied to the 5 and 3 prime ends of the molecule, which is then monitored. Force changes are then correlated with structural features. The pulling experiments, in collaboration with Anne Simon, are being correlated to simulated steered molecular dynamics, which enables the visualization of the unfolding events of the molecule as a function of the pulling speed and forces applied. Coarse-grained and explicit solvent techniques are being used to elucidate the structural characteristics. This technique offers a unique methodology to the understanding of RNA structure and the characteristics of various RNA motifs found in the structure. Mutations in the serine/threonine kinase BRAF are found in more than 60% of melanomas. The most prevalent melanoma mutation is BRAF(V600E), which constitutively activates downstream MAPK signalling. Vemurafenib is a potent RAF kinase inhibitor with significant clinical activity in BRAF(V600E)-positive melanoma tumours. However, patients rapidly develop resistance to vemurafenib treatment. One resistance mechanism is the emergence of BRAF alternative splicing isoforms leading to elimination of the RAS-binding domain. In this study we identified interference with pre-mRNA splicing as a mechanism to combat vemurafenib resistance. We found that small-molecule pre-mRNA splicing modulators reduce BRAF3-9 production and limit in-vitro cell growth of vemurafenib-resistant cells. In xenograft models, interference with pre-mRNA splicing prevents tumour formation and slows growth of vemurafenib-resistant tumours. Our results, in collaboration with Tom Misteli, identify an intronic mutation as the molecular basis for a RNA splicing-mediated RAF inhibitor resistance mechanism and we identifed premRNA splicing interference as a potential therapeutic strategy for drug resistance in BRAFmelanoma. Previous methods for comparative pseudoknot analysis mainly focus on simultaneous folding and alignment of RNA sequences. Little work has been done to align two known RNA secondary structures with pseudoknots taking into account both sequence and structure information of the two RNAs. This research, in collaboration with Jason Wang, involves the development of a novel method for aligning two known RNA secondary structures with pseudoknots. A partition function methodology is used to calculate the posterior log-odds scores of the alignments between bases or base pairs of the two RNAs with a dynamic programming algorithm. The posterior log-odds scores are then used to calculate the expected accuracy of an alignment between the RNAs. The goal is to find an optimal alignment with the maximum expected accuracy. A heuristic is developed to achieve this goal. The performance of the method was investigated and compared with existing tools for RNA structure alignment. The method has been implemented in a tool named RKalign, which is freely accessible on the Internet. The Zika virus is an emerging threat in the world. Although mostly prevalent in tropical zones it appears to be spreading to more temperate climates in the northern hemisphere due to the female Aedes aegypti mosquito. Warnings have been issued to pregnant women due to the potential for the virus to affect fetal development e.g. microcephaly. Zika virus is a Flavivirus and is related to the dengue viruses as well as other viruses in the Flaviviridae family. Due to our recent collaborations with R. Padmanabhan, and publications on the dengue virus, we collaborating on determining the structural characteristics of the virus some of which appear to be similar to the dengue structure. A minigenome is being constructed to further elucidate the mechanisms involved in Zika viral replication and translation. We are also pursuing, in collaboration with Shuo Gu, a comprehensive examination of potential RNA-RNA interactions that are found in cells. Miseq reads are being examined and correlated with computational analysis of potential interactions. The prevalence or lack thereof is being determined to enable a better understanding of how cellular RNA interacts with its cellular environment. A collaboration with Esta Sterneck's laboratory was recently initiated. Her lab investigates cell signaling pathways involved in breast and glioblastoma tumorigenesis with a focus on the transcription factor CCAAT/enhancer binding protein delta (CEBPD) using in vitro cell culture and in vivo mouse model systems. Using a transgenic mouse model of breast cancer, Her group has shown that CEBPD exhibits a dual role in mammary tumorigenesis. On the one hand, CEBPD prevents tumor multiplicity and on the other hand, CEBPD promotes distant lung metastases. In addition, CEBPD promotes stem-like cancer cells, which have been implicated in tumor metastasis and treatment resistance, in breast and glioblastoma tumor cells through regulation of various signaling pathways and stemness. We are working on understanding the structure of the mRNA coding for CEBPD using various computational techniques. Experimental work is planned to verify our predictions. In addition, strategies for targeting the message of CEBPD are necessary to downregulate CEBPD-mediated tumor progression signaling. As a tie in to our nanobiology project, our laboratory is developing approaches for RNAi therapeutics to knock down the CEBPD mRNA by delivering strategically designed RNA nanostructures as their own entities or in combination with lipid carriers.